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Presentation of fuzzy mathematics used in medical research Explanation of basic algorithms, partly in C++ Text:
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The purpose of this book is to present a wide variety of types of fuzzy mathematics used in medical research and in the modelling of diagnostic systems. Some techniques from fuzzy mathematics include fuzzy relation equations, group decision making, abstract algebra, clustering methods, belief functions, fuzzy measures, evidence theory, Sugero integrals, abduction, automata theory, genetic algebras, and hypergraphs. Applications to medicine include medical diagnosis, bone mineral density, stroke pathogenesis, clinical monitoring, and neuronal cell-assemblies. The five basic algorithms for data analysis (clustering based on fuzzy equivalence relations, fuzzy c-means algorithm, s olving a system of fuzzy relational equations, calculating fuzzy measures, and calculating the combined basic probabilistic measure) are explained in the appendix. Some of these algorithms are translated into the programming language C++.
Inhaltsverzeichnis
Summary of the contents:
- Sets and Relations
- Fuzzy Relation Equations
- Group Decisions
- Clustering Techniques
- Belief Functions
- Fuzzy Abduction, Automata, Genetic Algebras, and Hypergraphs
- Appendix
Über den Autor / die Autorin
D.S. Malik is a Professor of Mathematics and Computer Science at Creighton University. He received his Ph.D. from Ohio University in 1985. He has published more than 45 papers and 18 books on abstract algebra, applied mathematics, fuzzy automata theory and languages, fuzzy logic and its applications, programming, data structures, and discrete mathematics.
